---
language:
- ga
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Ga 4000 - Callum Canavan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: ga-IE
      split: test
      args: ga-IE
    metrics:
    - name: Wer
      type: wer
      value: 64.32276657060518
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Small Ga 4000 - Callum Canavan

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3939
- Wer Ortho: 65.7126
- Wer: 64.3228

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.0174        | 7.58  | 500  | 1.1656          | 63.4346   | 60.4899 |
| 0.0009        | 15.15 | 1000 | 1.2670          | 62.3248   | 60.8069 |
| 0.0004        | 22.73 | 1500 | 1.3114          | 63.6974   | 62.2478 |
| 0.0002        | 30.3  | 2000 | 1.3408          | 64.0187   | 62.6225 |
| 0.0002        | 37.88 | 2500 | 1.3621          | 64.3692   | 63.0836 |
| 0.0001        | 45.45 | 3000 | 1.3791          | 64.3984   | 62.9971 |
| 0.0001        | 53.03 | 3500 | 1.3900          | 65.8294   | 64.4092 |
| 0.0001        | 60.61 | 4000 | 1.3939          | 65.7126   | 64.3228 |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1